Numerical Data Modelling and Classification in Marine Geology by the SPSS Statistics

摘要

The paper focuses on the geostatistical analysis of the data set on thePhilippine archipelago. The research question is understanding variability inseveral geospatial parameters (geology, geomorphology, tectonics andbathymetry) in different segments of the study area. The initial data set wasgenerated in QGIS by digitizing 25 cross-sectioning profiles. The data set? contained information on the geospatial parametersin the samples by profiles. Modelling and statistical analysis were performedin SPSS IBM Statistics software. The analysis of the topography shows strongvariability of the elevations in the samples with the extreme depths in thecentral part of the study area (profile 13 with -9,400 m) and highestelevations in its south-western part (profile 17 with 1950 m). The analysis ofthe geological classes and lithology shows maximal samples of the basicvolcanic rocks (40,40%) followed by mixed sedimentary consolidated rocks (31,90%). Pairwise analysis of the sediment thickness and slope aspect demonstratescorrelation between these two variables with the maximal sediment layer in theprofiles 1-4 crossing the Philippines. The hierarchical dendrogram clusteringof the bathymetry by three approaches shown maximal correlation of 5 clusterscontaining profile groups: 12-18 (centre), 22-25 (south-west), 1-2 (north), 7-8(north-east), 19-21 (south-west). Other profiles show lesser similarities inthe bathymetric patterns. The forecasting models were computed for thegeospatial variables showing gradual increase in the gradient angles southwardsand increased values for the sediment thickness in the north. Technically, theresults proved effectiveness of the SPSS application of the geological data modelling.The paper focuses on the geostatistical analysis of the data set on thePhilippine archipelago. The research question is understanding variability inseveral geospatial parameters (geology, geomorphology, tectonics andbathymetry) in different segments of the study area. The initial data set wasgenerated in QGIS by digitizing 25 cross-sectioning profiles. The data set? contained information on the geospatial parametersin the samples by profiles. Modelling and statistical analysis were performedin SPSS IBM Statistics software. The analysis of the topography shows strongvariability of the elevations in the samples with the extreme depths in thecentral part of the study area (profile 13 with -9,400 m) and highestelevations in its south-western part (profile 17 with 1950 m). The analysis ofthe geological classes and lithology shows maximal samples of the basicvolcanic rocks (40,40%) followed by mixed sedimentary consolidated rocks (31,90%). Pairwise analysis of the sediment thickness and slope aspect demonstratescorrelation between these two variables with the maximal sediment layer in theprofiles 1-4 crossing the Philippines. The hierarchical dendrogram clusteringof the bathymetry by three approaches shown maximal correlation of 5 clusterscontaining profile groups: 12-18 (centre), 22-25 (south-west), 1-2 (north), 7-8(north-east), 19-21 (south-west). Other profiles show lesser similarities inthe bathymetric patterns. The forecasting models were computed for thegeospatial variables showing gradual increase in the gradient angles southwardsand increased values for the sediment thickness in the north. Technically, theresults proved effectiveness of the SPSS application of the geological data modelling.